Roadside LiDAR Sensor Configuration Assessment and Optimization Methods for Vehicle Detection and Tracking in Connected and Automated Vehicle Applications

Abstract

This paper develops an assessment and optimization model for configuring roadside LiDAR (Line Detection and Ranging) installation. More specifically, an analytic and a simulation model have been developed to analyze the detection blind zones and their impact on vehicle detection and tracking capabilities in Connected and Automated Vehicle (CAV) applications. The proposed model can derive the area and height of the detection blind zones from a given roadside LiDAR location and road geometry. Evaluation metrics are also proposed to assess the severity of the blind zone including laser beam density, blind zone height and duration, vehicle trajectory missing rate and duration. The simulation model can be used to evaluate and identify optimal configurations for different installation scenarios. To validate the proposed model, the 15-min US101 NGSIM (Next Generation SIMulation) dataset was used for validating the proposed model. Different configuration settings were simulated and compared. The evaluation results demonstrate the capabilities of the proposed models in planning for optimal roadside LiDAR sensor installation for vehicle detection and tracking.